Inspiration

Nowadays, people are trying to balance their nutrient intakes and develop better eating routines. Further, there are people who have some common food allergy such as milk allergy, eggs allergy, fish allergy, shellfish allergy, tree nuts allergy, peanuts allergy, wheat allergy, and soybeans allergy. When people who have food allergies eat the food that they should avoid by accident, their lives can be in danger.

Thus, we would like to develop a machine learning model and app that can provide information about the amount of energy, fat, protein, and fiber for the food people pick. By providing such information, people can plan their amount of food intake better. Further, our AI/ machine learning model also suggests recipes based on people's food allergy.

What it does

There is an AI virtual assistant that can answer some questions that are about food and health issues. Users upload photos of their food into this website and the machine learning will extract the text on the food label. After that, it provides nutrient facts about the food such as amount of energy, fat, protein, and fiber. Further, based on the food, the machine learning model can suggest the recipes. Users can filter recipes such as gluten free, diary free, soy free etc.

How we built it

  • We built the AI virtual Assistant using Google Cloud
  • We built the machine learning model that reads food label and split out the food facts as well as food recipes based on Google Cloud, Edaman

Challenges we ran into

We had an issue to come up with the idea for the challenge. We also had challenge to debug the codes.

Accomplishments that we're proud of

We were able to build the app with cool interface. We were able to build a virtual assistant and machine learning model that read food label, split out food facts, and recipes.

What we learned

We learnt to build virtual assistant using Google Cloud. We were able to learn more about Edaman.

What's next for Nutrizen

We would like to suggest more different types of food.

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